Instructions to use ZibinDong/ActionCodec-5e-RVQft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZibinDong/ActionCodec-5e-RVQft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ZibinDong/ActionCodec-5e-RVQft", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZibinDong/ActionCodec-5e-RVQft", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3189573ebcfef60d6924f142f4787b8397136388433a27ee013dad742b5dd92
- Size of remote file:
- 197 MB
- SHA256:
- 18045bfa8f9fced073bc6519191c76b23b26e3fd687ca6353fec2ef3d61b3c13
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